Lead Referral Interface for Real-Time eCRM Duplicate Detection
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Solution Overview
Problem
Conventional enterprise customer relationship management (eCRM) platforms are inefficient in interfacing with external data sources, leading to manual and time-consuming data upload processes, duplication of data entries, inability to detect existing records, and lack of real-time data synchronization and tracking of lead referrals.
Innovation Solution
A lead referral management (LRM) computing device that facilitates real-time data synchronization with eCRM platforms by directly accessing and comparing data through API calls, enabling immediate detection of duplicate entries and automatic data entry, while performing checks for existing relationships and compliance with Do-Not-Solicit regulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual data upload processes are used in conventional eCRM platforms, then data can be entered into the system, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The system performs preliminary actions by automatically detecting and comparing lead referral data against existing records before completing the upload process. The LRM computing device initiates API calls to check for existing relationships and duplicates proactively, so that when data needs to be uploaded, the system is already prepared and can immediately synchronize without manual intervention.
Solution Approach 2:
The system enables self-service by automating the entire data synchronization process without requiring user intervention. The LRM computing device automatically interfaces with external data sources, performs data comparison, detects duplicates, and completes uploads to the eCRM platform autonomously, eliminating the need for manual data entry and upload operations.
2Reliability
If conventional eCRM platforms store data without real-time synchronization, then data can be maintained in the system, but duplicate entries cannot be detected and data becomes stale
Solution Approach 1:
The system implements feedback mechanisms where the LRM computing device continuously monitors data changes in external sources, compares them against existing eCRM records, and automatically triggers synchronization processes. This real-time feedback loop ensures that data accuracy is maintained by detecting and preventing duplicate entries before they are stored, while keeping the eCRM platform synchronized with the latest information.
Solution Approach 2:
The system performs preliminary data comparison and validation checks before data is stored in the eCRM platform. The LRM computing device proactively queries external data sources and compares incoming data against existing records to identify duplicates in advance, preventing duplicate entries from being stored and ensuring data reliability.
3Ease of operation
If users manually check for existing lead referrals before uploading, then some duplicates may be avoided, but the process becomes even more time-consuming and complex
Solution Approach 1:
The system performs self-service by automatically conducting all verification processes without user involvement. The LRM computing device autonomously interfaces with external data sources, performs comprehensive data comparison, detects duplicates, and manages the entire upload process, eliminating the need for users to manually verify existing records and significantly simplifying the operation.
Solution Approach 2:
The LRM computing device acts as an intermediary between external data sources and the eCRM platform, handling all complex verification and comparison operations. This intermediary automatically manages the data synchronization process, performing checks that would be time-consuming for users to do manually, thereby simplifying the user experience while maintaining data integrity.
4Manufacturing precision
If eCRM platforms process data through multiple databases for translation and reformatting, then data can be properly stored, but the process takes 10-30 minutes and requires multiple users
Solution Approach 1:
The system performs preliminary data transformation and validation operations before data needs to be stored. The LRM computing device proactively retrieves data from external sources, performs necessary formatting and translation operations in advance, and prepares data for immediate insertion into the eCRM platform, eliminating the need for lengthy multi-database processing cycles.
Solution Approach 2:
The system extracts and consolidates the complex data transformation operations into a single streamlined process handled by the LRM computing device. Instead of routing data through multiple databases for sequential processing, the LRM device performs all necessary formatting, translation, and validation operations in one integrated step, dramatically reducing processing time while maintaining formatting accuracy.
Data Source
AI summary
A system for real-time data synchronization within a database platform may be provided. The system includes a LRM computing device including a processor in communication with one or more data sources and an eCRM platform. The processor may be configured to (i) cause an input page to be displayed on a user computing device; (ii) create in real-time a query including an identifier received using the input page; (iii) initiate in real-time an API call including the query; (iv) cause, in real-time and using the API call, the eCRM platform and the one or more data sources to compare the identifier to lead referral information stored on the one or more data sources and the eCRM platform; and (v) in response to no match being found in the comparison, automatically create and store a lead referral data entry on the one or more data sources and the eCRM platform.